Lead AI Engineer (MLX)

Responsibilities

• Partner with cross-functional teams of engineers, research scientists, and product managers to deliver AI-powered products.
• Design, develop, test, and deploy AI software components, including foundation model training and LLM inference.
• Implement similarity search, guardrails, model evaluation, and observability systems.
• Leverage technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch.
• Introduce state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap of foundational AI systems.

Requirements

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field.
• 4+ years of experience developing AI and ML algorithms or technologies.
• Proficiency in programming with Python, Go, Scala, or Java.

Preferred Qualifications

• 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, GCP, or Azure).
• Experience designing and supporting AI services.
• Expertise in LLM Inference, Similarity Search, VectorDBs, Guardrails, or Memory.
• Experience optimizing training and inference software for hardware utilization and cost efficiency.
• Ability to apply novel research and scientific publications to production environments.

About the Company

Capital One is an industry leader in using machine learning to create real-time, personalized customer experiences. We are committed to building world-class applied science and engineering teams to deliver breakthrough product experiences and scalable, high-performance AI infrastructure.